PXD034773-1

PXD034773 is an original dataset announced via ProteomeXchange.

Title	Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes
Description	CD4+ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on MHC-II molecules. The high polymorphism of MHC-II genes represents an important hurdle towards accurate predictions of CD4+ T-cell epitopes in different individuals and different species. Here we generated and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to determine the binding motifs of 88 MHC-II alleles across human, mouse, cattle and chicken. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse binding mode in MHC-II ligands. We then developed a machine learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T-cell epitopes, as demonstrated by the identification of several viral and bacterial epitopes following the aforementioned reverse binding mode.
HostingRepository	PRIDE
AnnounceDate	2023-04-07
AnnouncementXML	Submission_2023-04-07_10:24:40.272.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	MichalBassani-Sternberg
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	No PTMs are included in the dataset
Instrument	Q Exactive HF

Revision	Datetime	Status	ChangeLog Entry
0	2022-06-21 01:52:27	ID requested
⏵ 1	2023-04-07 10:24:40	announced

Dataset with its publication pending

ProteomeXchange project tag: Human Immuno-Peptidome Project (HUPO-HIPP) (B/D-HPP), Biology/Disease-Driven Human Proteome Project (B/D-HPP), Human Proteome Project

submitter keyword: HLA-II binding motifs, machine learning predictions, HLA-II peptides

MichalBassani-Sternberg
contact affiliation	Ludwig Institute for Cancer Research Lausanne Centre de recherche Agora Rue du Bugnon 25A CH-1011 Lausanne
contact email	michal.bassani@chuv.ch
lab head
MichalBassani-Sternberg
contact affiliation	UNIL/CHUV
contact email	michal.bassani@chuv.ch
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2023/04/PXD034773

PRIDE project URI

• PRIDE
  1. PXD034773
     1. Label: PRIDE project
     2. Name: Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes